Linear-time training of nonlinear low-dimensional embeddings.
Max VladymyrovMiguel Á. Carreira-PerpiñánPublished in: AISTATS (2014)
Keyphrases
- low dimensional
- nonlinear manifold learning
- high dimensional
- dimensionality reduction
- manifold learning
- high dimensional data
- linear dimensionality reduction
- principal component analysis
- low dimensional manifolds
- euclidean space
- vector space
- nonlinear dimensionality reduction
- data points
- nonlinear manifold
- training set
- low dimensional spaces
- dimension reduction
- gaussian process latent variable models
- training samples
- feature space
- linear subspace
- multidimensional scaling
- graph embedding
- input space
- manifold embedding
- machine learning
- test set
- training algorithm
- latent space
- supervised learning
- distance measure
- appearance manifolds
- training examples
- input data